The retail industry is a complex and dynamic segment where many factors influence the success. A number of metrics, or key performance indicators (KPIs), help improve the understanding and performance of a location and its space. This overview explains the most important metrics for retailers.
Frequency Data 2.0: Revealing Successes and Potential
To measure the success of their own business and optimize their space, many retailers are now using high-precision 3D sensors combined with an intelligent analytics platform to make activities in their space as transparent as possible. In particular, accurate measurement through path analysis is required to accurately assess conversion potential. The following metrics are particularly relevant:
Visits / Footfall
The number of visits to a store or shop. This metric is a minimum standard for visitor counting and is currently tracked by almost all stores. Caution should be exercised, however, as the number may be only partially meaningful in certain areas.
Occupancy
This metric shows the average number of people in the store at any given time. It can reveal fluctuations in customer demand and help with staffing. It is important to look at occupancy over time, such as on an hourly, daily, or weekly basis. This can help identify peaks and lows.
Passersby / Footfall Potential
The number of passers-by who could potentially visit a store, either because they are passing by or because they are already in the mall. Companies like hystreet use laser sensors to measure footfall in city centers and provide this data to stores.
Average Dwell Time
The average amount of time a person spends in a store. This can help gauge customer interest in a store's offerings.
Capture Rate
The ratio of the number of passers-by to the number of visits. It shows how well potential visitors are actually being captured into the store.
Conversion Rate
This relative figure, usually expressed as a percentage, shows the ratio of the number of visitors to the number of actual purchases made by all visitors. It is calculated by dividing the actual number of buyers (e.g. 50 people throughout the day) by the total number of visitors for the day (e.g. 2,000 people). The resulting percentage represents the conversion rate - in our example, it would be 2.5 percent. The higher this number, the more people actually made a purchase. The goal of all retailers is to increase the conversion rate, for example by providing better service, which can be optimized by the sensalytics CX Engine.
Revenue Metrics: How good are my actual sales?
Of course, not only anonymously measured occupancy and movement patterns of individuals play a role in assessing business success, but also concrete sales and revenue figures. Here are the most important KPIs:
Total Net Revenue
Net revenue. This is a fundamental measure of a store's success and shows the total value of sales after returns and discounts have been deducted.
Number of Purchases
The number of purchases made by customers in a given period, such as a business day. This number is used to calculate the conversion rate.
ATV (Average Transaction Value)
The average transaction value shows the average amount a customer spends on a single purchase.
UPT (Units Per Transaction)
The average number of items a customer purchases per transaction. A higher UPT can indicate a successful cross-selling strategy and a targeted assortment for the retailer's target audience.
Relevant metrics for outlet centers and malls
In malls and outlets, retail analytics are becoming increasingly relevant to the success of tenants and the malls in general. Frequency alone has become obsolete and several other metrics are now important. These include:
Stores per visitor
The average number of stores a visitor visits in a mall or shopping center. This number provides insight into the overall shopping behavior of shoppers. The higher the value, the more vibrant the center as a whole.
Visitor Flow Correlation
Visitor Flow Correlation is a KPI specifically developed by sensalytics that reveals valuable insights: the correlation of visits between stores. By combining visitor source (information indicating where a person is coming from) and visitor destination (information indicating where a person is going), it is possible to determine the percentage of visitors who have previously visited a particular store. This metric can be clustered by segment, floor and individual store, giving center managers and property operators insight into store offerings and overall mall or outlet performance.
Retail Analytics as a Central Component of Business Optimization
All of these metrics demonstrate that today, more than ever, intelligent and highly accurate analytics systems are needed to consolidate and correlate key metrics on a single platform. Retail analytics provides a solid foundation for operational and strategic optimization processes, leaving no room for speculation about success or failure. Collected and analyzed data helps plan staffing, improve the customer experience, and increase a retailer's profitability. In short, they are essential to every store today.
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